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Journal ArticleDOI

Detecting Differential Item Functioning Using Logistic Regression Procedures

TLDR
In this paper, a logistic regression model for characterizing differential item functioning (DIF) between two groups is presented and a distinction is drawn between uniform and non-uniform DIF in terms of the parameters of the model.
Abstract
A logistic regression model for characterizing differential item functioning (DIF) between two groups is presented. A distinction is drawn between uniform and nonuniform DIF in terms of the parameters of the model. A statistic for testing the hypothesis of no DIF is developed. Through simulation studies, it is shown that the logistic regression procedure is more powerful than the Mantel-Haenszel procedure for detecting nonuniform DIF and as powerful in detecting uniform DIF.

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Book

Methods and Data Analysis for Cross-Cultural Research

TL;DR: This comprehensive guide, which covers all major issues in the field, presents cross-cultural methodology in a practical light and discusses the design and analysis of quasi-experiments - the dominant framework for cross- cultural research.
Journal ArticleDOI

A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF

TL;DR: In this paper, a model-based modification of the standardization index based upon a multidimensional IRT bias modeling approach is presented that detects and estimates DIF or item bias simultaneously for several items.
Journal ArticleDOI

lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations

TL;DR: The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program, and a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures.
Journal ArticleDOI

Methodology Review: Statistical Approaches for Assessing Measurement Bias

TL;DR: In this paper, a review of statistical methods for detecting measurement bias in psycho-logical and educational tests is presented, which employs a conceptual framework that distin guishes methods of detecting measuring bias based on either observed or unobserved conditional invariance models.
References
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Journal ArticleDOI

Multivariate Statistical Methods

TL;DR: In this article, a text designed to make multivariate techniques available to behavioural, social, biological and medical students is presented, which includes an approach to multivariate inference based on the union-intersection and generalized likelihood ratio principles.
Book

Multivariate statistical methods

TL;DR: In this article, a text designed to make multivariate techniques available to behavioural, social, biological and medical students is presented, which includes an approach to multivariate inference based on the union-intersection and generalized likelihood ratio principles.
Journal ArticleDOI

The area between two item characteristic curves

TL;DR: It is shown that when thec parameters are unequal, the area between two ICCs is infinite and the significance of the exact area measures for item bias research is discussed.
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